Who is AiDash?
AiDash is making critical infrastructure industries climate-resilient and sustainable with satellites and AI. Using our full-stack SaaS solutions, customers in electric, gas, and water utilities, transportation, and construction are transforming asset inspection and maintenance - and complying with biodiversity net gain mandates and carbon capture goals. Our customers deliver ROI in their first year of deployment with reduced costs, improved reliability, and achieved sustainability goals. Learn more at www.aidash.com.
What will you do?
Develop and refine models to address environmental challenges like wildfire detection and flood mapping, utilising diverse satellite imagery and data types for comprehensive analysis.
Improve the accuracy and efficiency of 2D and 3D geospatial data processing using machine learning, and enhance AI and vision systems for effective large-scale data analysis.
Streamline computational processes for faster model performance, design autonomous systems for smart decision-making, and continuously update models to ensure relevance. Drive innovation through research collaborations and the pursuit of new ideas for AI/ML advancements.
Collaborate with cross-functional teams, including engineering, product, and business units, to integrate data science into diverse projects.
Lead and mentor junior data scientists and analysts, providing guidance and oversight on their projects.
What are we looking for?
Bachelors or Master's in Computer Science, Data Science, or a related field.
Minimum of 7+ years of experience in a data science role, with a strong emphasis on machine learning and statistical analysis.
Experience in building scalable feature extractors on image datasets.
Experience in delivering scalable AI/ML, computer visions and statistical solutions on large image datasets.
Experience in data analytics methodologies and tools i.e. Python, SQL and data visualisations.
Experience of cloud-based platforms i.e., Azure, AWS, GCP and big data technologies i.e., Hadoop, Spark is highly desirable.
Proficient in machine learning libraries and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
Excellent problem-solving and analytical skills.
Demonstrated ability to lead projects and work effectively in a team environment.
Strong communication skills, with the ability to explain complex concepts to non-technical audiences.
What other experience will make you a great candidate?
Experience in storing, processing large scale geospatial datasets on scale and familiarity of corresponding tech stacks.
Experience in building AI/ML and computer vision solution of geospatial datasets i.e., Satellite, Lidar.
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